Tera Marie Green
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Human-Computer Interaction top 10%
- Experimental and Cognitive Psychology
- Sociology and Political Science
- Co-authors
- William RibarskyBrian FisherRemco ChangCaroline ZiemkiewiczDong Hyun JeongSteve DiPaolaRoss MaciejewskiJohn C. Dill
- Topics
- Data Visualization and Analytics (10 papers)Visual and Cognitive Learning Processes (4 papers)Geographic Information Systems Studies (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionHuman-Computer InteractionGeography, Planning and Development
- Partner nations
- CanadaUnited States
In The Last Decade
Tera Marie Green
12 papers receiving 335 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 272
- Artificial Intelligence 118
- Human-Computer Interaction 45
- Experimental and Cognitive Psychology 39
- Sociology and Political Science 34
Countries citing papers authored by Tera Marie Green
This map shows the geographic impact of Tera Marie Green's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tera Marie Green with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tera Marie Green more than expected).
Fields of papers citing papers by Tera Marie Green
This network shows the impact of papers produced by Tera Marie Green. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tera Marie Green. The network helps show where Tera Marie Green may publish in the future.
Co-authorship network of co-authors of Tera Marie Green
This figure shows the co-authorship network connecting the top 25 collaborators of Tera Marie Green. A scholar is included among the top collaborators of Tera Marie Green based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tera Marie Green. Tera Marie Green is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 1 | |
| 3 | 20 | |
| 4 | 7 | |
| 5 | 15 | |
| 6 | 5 | |
| 7 | 63 | |
| 8 | 100 | |
| 9 | 60 | |
| 10 | 7 | |
| 11 | 65 | |
| 12 | Correlations between Emotion Regulation, Learning Performance, and Cortical Activity | 1 |
About Tera Marie Green
Tera Marie Green is a scholar working on Computer Vision and Pattern Recognition, Geography, Planning and Development and Experimental and Cognitive Psychology, having authored 12 papers that have together received 352 indexed citations. Recurring topics across this work include Data Visualization and Analytics (10 papers), Visual and Cognitive Learning Processes (4 papers) and Geographic Information Systems Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (272 citations), Human-Computer Interaction (45 citations) and Geography, Planning and Development (34 citations). Tera Marie Green has collaborated with scholars based in Canada and United States. Frequent co-authors include William Ribarsky, Brian Fisher, Remco Chang, Caroline Ziemkiewicz, Dong Hyun Jeong, Steve DiPaola, Ross Maciejewski, John C. Dill and Kayvan Najarian. Their work appears in journals such as IEEE Computer Graphics and Applications, interactions and Topics in Cognitive Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.